Research Article | OPEN ACCESS
3-Layered Bayesian Model Using in Text Classification
Chang Jiayu and Hao Yujie
Department of Computer Science and Engineering, University of Electronic Science and
Technology of China, Chengdu 611731, China
Research Journal of Applied Sciences, Engineering and Technology 2013 3:986-989
Received: June 23, 2012 | Accepted: July 28, 2012 | Published: January 21, 2013
Abstract
Naive Bayesian is one of quite effective classification methods in all of the text disaggregated models. Usually, the computed result will be large deviation from normal, with the reason of attribute relevance and so on. This study embarked from the degree of correlation, defined the node’s degree as well as the relations between nodes, proposed a 3-layered Bayesian Model. According to the conditional probability recurrence formula, the theory support of the 3-layered Bayesian Model is obtained. According to the theory analysis and the empirical datum contrast to the Naive Bayesian, the model has better attribute collection and classify. It can be also promoted to the Multi-layer Bayesian Model using in text classification.
Keywords:
3-layered Bayesian model, coefficient of correlation, degree, matrix of correlation, naive Bayesian,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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